Two Distinct Tracks
Dedicated fundamental & quantitative tracks.
Most members follow the same general pitch process.
Independent, student-run fund with sector ownership, public-market pitches & a selective quant track.
A pre-college fund where students lead sector research, publish pitches & manage real capital with industry guidance.
Analysts build sector expertise & develop stock pitches using a course built by finance professionals, research tools & guidance from industry leaders.
Explore insights Quant ResearchRanking models, signal design & algorithmic execution, developed and reviewed as formal research.
See the track StructureA student-run team of sector heads & executives, advised by industry leaders and a Risk Advisory Board.
Meet the teamEvery analyst selects one of two research tracks, then follows the same disciplined process.
Analysts begin by choosing one of White Mane's two research tracks.
Join a sector team & build industry expertise.
Learn accounting, valuation, research & pitch development.
Develop and present an original stock pitch.
The strongest pitches are reviewed by the executive board & industry advisors.
Track performance, news, valuation & thesis changes.
Work within White Mane's specialized quant team.
Learn statistics, Python, market data & backtesting.
Develop and present an original model, signal or strategy.
The strongest ideas are reviewed by the executive board & industry advisors.
Track signal performance, portfolio impact & changing conditions.
Share work through White Mane Insights & grow into leadership.
Dedicated fundamental & quantitative tracks.
Most members follow the same general pitch process.
Analysts build sector expertise through continued coverage.
Research is often one-off & less specialized.
Quant is a dedicated research arm focused on data, signals & backtesting.
Quant work is often limited or absent.
Training, sector review, executive review, monitoring & publication.
Members often pitch once & move on.
Our most selective track. Members design ranking systems, study stochastic models & explore algorithmic execution. Coding and statistical reasoning required.